Skip to main content

Objective assessment of mental stress in individuals with different levels of effort reward imbalance or overcommitment using heart rate variability: a systematic review



Workloads are increasing and could cause mental stress, e.g., in the form of subjective effort reward imbalance (ERI) and overcommitment (OC). The heart rate variability (HRV) is a valid method for objective monitoring of workload. The aim of this project is to systematically evaluate the literature on HRV as an objective indicator for mental stress in individuals with different levels of ERI or OC.


A systematic literature review examining HRV of employees in accordance with the Preferred Reporting Items for Systematic Reviews and Meta-Analysis (PRISMA) statement for reporting systematic reviews was performed. Electronic databases used were PubMed, Ovid, Cochrane Libary, Scopus and Web of Science, PsyInfo, Psyndex, and Livio. Only articles from 2005 to 2021 were included. Inclusion criteria were case-control studies, intervention studies, cross-sectional studies, or longitudinal studies with different levels of ERI and/or OC, >10 participants in each group, measurement of 24h HRV by using Holter ECG or chest belt, and full-text in English or German language. The methodological quality was evaluated by using a modified STARD for HRV.


Five studies matched the inclusion criteria by using HRV (24-h ECG) with a different HRV analysis at day and night. It showed an adaptation of HRV with higher ERI or OC with reduced parasympathetic HRV parameters, but the studies were not comparable.


There is a need for occupational health studies that examine strains and stress of different employees with predominantly mental stress. The well-established parasympathetic mediated HRV parameters seem to be suitable parameters to objectify the stress.

Peer Review reports


No matter whether it is an obligation or vocation, work remains a central topic for every individual. In this context, we are facing a working society in a state of ongoing change. The world of work is becoming more diverse, more digital, and more global. It provides new opportunities, but also risks. Currently, four generations are working together in many branches [1]. From baby boomers to Generation X and Y to Generation Z, which could not be more different. They have different claims on work and leisure time. This also results in different ideas of loyalty and flexibility [1]. As a result, stress in the workplace can be perceived differently and making occupational health assessments necessary on an ongoing basis and requiring constant reassessment.

An established subjective assessment instrument for mental stress is the effort reward imbalance model (ERI) according to Siegrist [2]. The ERI questionnaire reveals satisfactory psychometric properties and can be recommended for further research in the era of economic globalization [3]. The model is used to determine the relationship between the work performance/overcommitment (effort) and the experienced reward [2]. The baseline assumption of the model is that an imbalance between the lack of occupational rewards and the expenditures can lead to adverse stress reactions. If the reward perceived after work performance becomes insufficient, a specific form of social crisis may occur—the so-called gratification crises [2]. Here, individually and socially expected relationships are disappointed. The concept of ERI is exposed to enormous subjective individual variations in a defined work environment and is evaluated very differently between individuals [2]. In this regard, ERI values below 1.0 indicate a balance between effort and reward; values above 1.0 indicate an imbalance of effort and reward [2, 3]. Various studies have shown, for example, an increased risk of cardiovascular disease [2, 4] and the increased occurrence of psychological symptoms such as depression [5, 6] in association with a high ERI ratio.

The overcommitment (OC) subscale of the ERI describes the tendency to overspend oneself without regard to one’s resources [2]. So it is an intrinsic, person-related factor. Overcommitment is also associated with health risks. It is associated with vital exhaustion [7] or burnout [8]. Furthermore, it can lead to musculo-skeletal disorders [9], inflammation [10], or impaired immunocompetence [10].

Heart rate variability (HRV) analysis is a possible method for objective monitoring of workload, e.g., in the context of an occupational health examination [11]. Guidelines define HRV as variations over time between consecutive heartbeats. They also see HRV as a very sensitive indicator of dysregulation of the autonomic nervous system (ANS) [12, 13]. It is a non-invasive measurement to evaluate the stress of the cardiovascular system [14]. The vagus nerve, which stimulates the atria of the heart and modulates the self-sustaining sinus rhythm of the sinus or Keith flack node, is an essential part of HRV tone. The interaction between sympathetic and parasympathetic nervous systems can be estimated as different demands with the analysis of HRV [13]. Parasympathetic activity dominates in rest and recovery phases of the body, whereas sympathetic activity dominates in chronic state of stress [13]. HRV analysis differs time, frequency, and nonlinear domains. An overview of HRV metric is given by [14, 15], or the current guidelines [12, 13]. The ANS is involved in stress regulation, so (work-related) chronic stress has been associated with reduced HRV and reduced parasympathetic modulation [16]. For example, HRV markers of vagal function are the root mean square of successive differences (RMSSD), percentage of successive NN intervals that differ by more than 50 ms (pNN50), high frequency power (HF), and standard deviation of point plot to the transverse diameter (SD1) [13]. But other parameters (e.g. low frequency power (LF), LF/HF ratio (LF/HF)) are without clear assignment and can be influenced by the sympathetic and parasympathetic nervous system [13]. Analyzing HRV, it should be noted that there is an age dependency of HRV [17], and it is also necessary to know which recording time is necessary (e.g., 24-h, short-term (5 min), and ultrashort-time (<5 min)) for according parameters and which parameters are relevant for the question to be determined [18].

The aim of this project was to systematically evaluate the literature on heart rate variability as an objective indicator for mental stress in individuals with different levels of ERI and/or OC. We hypothesized that a high ERI ratio or high OC is associated with an increased reduction in vagal tone.


This systematic literature review examined heart rate variability in context of effort reward imbalance and/or overcommitment in accordance with the Preferred Reporting Items for Systematic Reviews and Meta-Analysis (PRISMA) statement for reporting systematic reviews [19]. The electronic databases PubMed, Ovid, Cochrane Library, Scopus and Web of Science, PsyInfo, Psyndex, and Livio were used. The deadline was February 01, 2021. Search terms were defined as “overcommitment” OR “effort reward imbalance” AND “heart rate variability” OR “HRV” OR “cardiac autonomic control” OR “autonomic function” OR “parasympathetic activity” OR “parasympathetic nervous system” OR “cardiac vagal tone” OR “autonomic cardiac modulation” OR “vagus nerve” OR “vagal tone” OR “vagal activity” OR “coefficient of variation” OR “autonomic nervous system OR “sympathetic” OR “parasympathetic” OR “sympathetic nerve activity” OR “neural control” OR “activation of the sympathetic nervous system”. Only articles from 2005 to 2021 were included. Inclusion criteria were studies with different levels of ERI and/or OC, more than 10 participants (in each group), measurement of HRV 24 h, recording of heart rate through Holter ECG or chest belt, full-text in English or German language, and human subjects. Papers with case-control studies, intervention studies, cross-sectional studies, or longitudinal studies were included.

Exclusion criteria were HRV assessment with pulse rate automatic or photoplethysmography, diagnosis of mental or neurological diseases, endocrine diseases (diabetes, thyroid gland disease), cardiac diseases, hypertension, other heart rhythm-related diseases, and intake of drugs influencing HRV. Review articles, guidelines, single-case studies, theses, dissertations, and scientific conference abstracts were also excluded. The national guideline on HRV does not suggest the method of pulse rate or photoplethysmography of measurement [14], so that was an exclusion criteria.

Next to the literature research, a hand search was performed by checking the reference lists of the included studies (no result). One study was included in the databases after the literature search (due to a subsequent publication). An overview of the procedure is shown in Fig. 1. The complete study protocol is available at Prospero

Fig. 1
figure 1

Flow chart in the context of the systematic literature search

The included articles were transferred to the reference manager Citavi 6 (Swiss Academic Software, Wädenswil, Switzerland) without duplicates. Two authors (B.T. and J.H.) independently screened titles and abstracts according to the inclusion and exclusion criteria. The full-text of each relevant article was obtained, which was independently screened by two authors (B.T. and J.H.). If no full-text was available, the authors were contacted. Disagreements were resolved through discussion with a third reviewer (I.B.).

The methodological quality of the research question relevant studies was evaluated using the Standard for Reporting Diagnostic Accuracy Studies (STARD) guidelines [20, 21], which follows the recommendations of [22] and [18]. All studies were also evaluated independently by two authors (B.T. and J. H.) using a modified STARD for HRV by [23]. It included 25 items (maximum of points). We have slightly modified two assessment tools [24], but the maximum score did not change. The items are shown in Table 1. Disagreement was solved by (I.B.) and discussion.

Table 1 Evaluation points (P) of STARDHRV followed by Dobbs et al. [23] and modified by Grässler et al. [24]

From the included studies, the changes in all HRV parameters used were collected. Due to the limited data available, a descriptive discussion of the results was conducted without further statistical analysis. Increases were marked with an upward arrow, decreases with a downward arrow, and no change with an arrow pointing to the left and right. Significant changes were marked with an asterisk. Table 2 explains the parameters used in the review and the affiliation to the ANS.

Table 2 Overview of the HRV parameters evaluated in the review and their importance


The initial search resulted in 649 records and included one study, which was published after literature research [25]. After removing duplicates and exclusions based on title and abstract, only five full-texts were assessed for eligibility. Four studies used ERI [26,27,28,29], and one study used OC [25]. The professional groups were different (four studies): nurses [26, 27], employees of different sectors/branches [28, 29], and kindergarten teachers [25]. Two studies studied the same subjects, but reported different HRV parameters in the two publications, so they were both listed [26, 27]. All studies came from Europe (Germany and Italy). An overview of the included studies is shown in Table 3. The literature search revealed five studies with HRV analysis using ERI and/or OC, but ECG recordings were too short (3 min, 45 min, 2 h, 18 h) or too long (36 h), so they were excluded from the review [30,31,32,33,34]. Only one study examined risk factors related to cardiovascular disease, but only with the glycemic status [28]. All studies examined daytime and nighttime separately. Subject populations varied widely, and ranged from 53 [26, 27] to 9937 [28]. All study protocols were different. Two studies used classification with the ERI ratio [26, 27] and one a cutoff of OC [25], and each compared the groups. One study divided into age groups, compared them with RMSSD as the only parameter, and included ERI as a coefficient [29]. One study averaged ERI and RMSSD and ran various model calculations. Glycemic status and the inflammation parameter CRP were also included [28]. One study examined only women [25], two with more than two-thirds [26, 27], and two with less than 20% [16, 29]. Where possible, no gender differences were found in the studies.

Table 3 Results of the systematic research

Outcome heart rate variability

One study used a chest belt [28], and the other four used classic Holter ECGs.

The time periods for HRV analysis varied widely among the studies. Borchini et al. analyzed 2 h of the 24 h recordings, each at the 5 different phases (working day working, non-working, night and resting day with day and night phase) [27]. The duration of HRV derivation in each phase was not standardized. Table 3 presents the outcome of all HRV measures.

Four studies used RMSSD as a marker of vagal function [25, 26, 28, 29]. RMSSD decreased with higher ERI or OC outcomes. It was significant for 24 h and night phase [25], overworking day, but not sleep [29], and also negative associated with ERI [28]. No significance was found in one publication [26]. The parasympathetic-associated parameter pNN50 decreased in kindergarten teachers with high overcommitment in 24 h and night phase [25]. For the SDNN (parasympathetic and sympathetic nervous system), SDANN and SDNN Index (both parameters without clear assignment to parasympathetic or sympathetic nervous system) at working day [26] and for SDNN in night phase [25] are decreased in subjects with higher ERI or OC. The frequency domain parameter HF showed the same tendency [25, 27]. The two studies that used LF and LF/HF showed opposite trends. LF and LF/HF increased at higher ERI [25], but also decreased [27]. The trend of HRV parameters looks adaptive to the stress situation related to higher ERI or OC.

One study found age-dependent effects for LF and HF at night. This study also examined work experience, which had no effect on HRV [25]. The study with age-related research found a lower RMSSD in higher ERI, which was most pronounced in employees aged 35–44 years [29].

Quality assessment

The study quality of HRV methodology was evaluated with STARDHRV [23] and modified according to [24]. The scores for all studies were 15 [28], 16 [25, 26], 17 [29], and 19.5 [27].

Full marks were achieved in all studies for points 1, 2, 9, 14, and 29. Zero points were found in the case of elevation points 5, 6, and 13 in all studies. The other points showed a heterogeneous allocation from 0 to 1. This evaluation is attached as Supplement 1.

Monitoring during the work could lead to movement artifacts, which limits the assessment. Three studies reported exclusion criteria about diseases and medication [25,26,27] and two did not report [28, 29]. Three studies performed a manual inspection of NN intervals [25,26,27]; other publications did not do so [28, 29]. Only one of the studies reported the percentages of adjusted material [29].

Summary of the results

The observed studies showed an adjustment of HRV by reduction of parasympathetic mediated HRV parameters thus at higher subjective stress (higher ERI or OC). The study quality of the HRV methodology was moderate. The average score for all studies was 16.7/25 points.


The purpose of the review is to systematically evaluate the literature on heart rate variability as an objective indicator for mental stress in individuals with different levels of ERI and/or OC.

All studies used HRV during work and examined day and night phases. The selected HRV parameters are able to provide information about the measured strain (effort reward imbalance and/or OC). It should be noted that there are different study protocols and different recording times, so these values are only comparable to a limited degree.

Comparisons and statements about cardiovascular risk factors cannot be made. No gender differences were found on the basis of the studies either.

Deficiencies were found in the methodological quality and in the quality of the study reports. The numbers of subjects are very small (except for one study), so a generalization is not possible.

A trend can be seen so that the predominantly parasympathetic mediated parameters (e.g., RMSSD, pNN50, HF) decreased as an adaptation to workload (high ERI or OC) with a decrease. HRV parameters with both parasympathetic and sympathetic influences also decreased (e.g., SDNN, SDANN) or increased (e.g., LF, LF/HF). This is concerning, especially if HRV cannot be adequately adjusted by nighttime sleep, which hypothesizes a lack of recovery. Nonlinear parameters were not used. Minor age-related effects and not effects of work experience of HRV parameters could be found; both should not be overinterpreted.


This systematic review shows that there is a high need and a great potential for occupational health studies among different professional groups with mental stress. HRV is a valid objective method for visualizing stress, i.e., for measuring strain [13]. We recommend the use of 24-h ECGs to evaluate the “night” recovery phase. For the assessment of mental stress, the parasympathetic dominant HRV parameters were shown to be effective markers for this. Other parameters (e.g., without clear assignment or nonlinear parameters) should be used as a complement.

Availability of data and materials

The data can be accessed via the corresponding author. They are archived at the corresponding university.



Age groups


Autonomic nervous system


Effort reward imbalance ratio


High frequency power


Heart rate


Heart rate variability


Low frequency power


Quotient between LF and HF power




Percentage of successive NN intervals that differ by more than 50ms


Prolonged high strain

RD :

Resting day


Recently high strain


Standard deviation of the average of NN intervals in 5-min segments


Standard deviation of all normal-to-normal R-R intervals

SDNN Index:

Mean of the 5-min standard deviation of the NN interval


Stable low strain


Working day


  1. Spielberg P. Generationenkonflikte am Arbeitsplatz: “Das Problem ist nicht unlösbar”. Dtsch Arztebl. 2019;116:A1194/B986/C974.

    Google Scholar 

  2. Siegrist J. Adverse health effects of high-effort/low-reward conditions: 0931. J Occup Health Psychol. 1996;1:27–41.

    Article  CAS  PubMed  Google Scholar 

  3. Siegrist J, Wege N, Pühlhofer F, Wahrendorf M. A short generic measure of work stress in the era of globalization: effort-reward imbalance. Int Arch Occup Environ Health. 2009;82:1005–13.

    Article  PubMed  Google Scholar 

  4. Dragano N, Siegrist J, Nyberg ST, Lunau T, Fransson EI, Alfredsson L, et al. Effort-Reward Imbalance at Work and Incident Coronary Heart Disease: A Multicohort Study of 90,164 Individuals. Epidemiology. 2017;28:619–26.

    Article  PubMed  PubMed Central  Google Scholar 

  5. Juvani A, Oksanen T, Salo P, Virtanen M, Kivimäki M, Pentti J, et al. Effort-reward imbalance as a risk factor for disability pension: the Finnish Public Sector Study. Scand J Work Environ Health. 2014;40:266–77.

    Article  PubMed  Google Scholar 

  6. Araújo TM de, Siegrist J, Moreno AB, De Jesus Mendes da Fonseca, Maria, Barreto SM, Chor D, Griep RH. Effort-reward imbalance, over-commitment and depressive episodes at work: evidence from the ELSA-Brasil Cohort Study. Int J Environ Res Public Health 2019. doi:

  7. Preckel D, von Kanel R, Kudielka BM, Fischer JE. Overcommitment to work is associated with vital exhaustion. Int Arch Occup Environ Health. 2005;78:117–22.

    Article  PubMed  Google Scholar 

  8. Violanti JM, Mnatsakanova A, Andrew ME, Allison P, Gu JK, Fekedulegn D. Effort-reward imbalance and overcommitment at work: associations with police burnout. Police Q. 2018;21:440–60.

    Article  PubMed  PubMed Central  Google Scholar 

  9. Joksimovic L, Starke D, v d Knesebeck O, Siegrist J. Perceived work stress, overcommitment, and self-reported musculoskeletal pain: a cross-sectional investigation. Int J Behav Med. 2002;9:122–38.

    Article  PubMed  Google Scholar 

  10. Siegrist J, Li J. Associations of extrinsic and intrinsic components of work stress with health: a systematic review of evidence on the effort-reward imbalance model. Int J Environ Res Public Health. 2016;13:432. .

    Article  PubMed  PubMed Central  Google Scholar 

  11. Järvelin-Pasanen S, Sinikallio S, Tarvainen MP. Heart rate variability and occupational stress-systematic review: 0650. Ind Health. 2018;56:500–11.

    Article  PubMed  PubMed Central  Google Scholar 

  12. Task Force of the European Society of Cardiology and the North American Society of Pacing and Electrophysiology. Heart rate variability. Standards of measurement, physiological interpretation, and clinical use: 0041. Eur Heart J. 1996;17:354–81.

    Article  Google Scholar 

  13. Sammito S, Thielmann B, Seibt R, Klussmann A, Weippert M, Böckelmann I. Guideline for the application of heart rate and heart rate variability in occupational medicine and occupational science: 0651. ASU Int. 2015.

  14. Sammito S, Böckelmann I. Analysis of heart rate variability. Mathematical description and practical application. [Analyse der Herzfrequenzvariabilität. Mathematische Basis und praktische Anwendung]. Herz. 2015;40(Suppl 1):76–84.

    Article  PubMed  Google Scholar 

  15. Shaffer F, Ginsberg JP. An Overview of Heart Rate Variability Metrics and Norms. Front Public Health. 2017;5:258.

    Article  PubMed  PubMed Central  Google Scholar 

  16. Jarczok MN, Koenig J, Wittling A, Fischer JE, Thayer JF. First evaluation of an index of low vagally-mediated heart rate variability as a marker of health risks in human adults: proof of concept. J Clin Med. 2019.

  17. Sammito S, Böckelmann I. Reference values for time- and frequency-domain heart rate variability measures. Heart Rhythm. 2016;13:1309–16.

    Article  PubMed  Google Scholar 

  18. Laborde S, Mosley E, Thayer JF. Heart rate variability and cardiac vagal tone in psychophysiological research - recommendations for experiment planning, data analysis, and data reporting. Front Psychol. 2017;8:213. .

    Article  PubMed  PubMed Central  Google Scholar 

  19. Moher D, Liberati A, Tetzlaff J, Altman DG. Preferred reporting items for systematic reviews and meta-analyses: the PRISMA statement. J Clin Epidemiol. 2009;62:1006–12.

    Article  PubMed  Google Scholar 

  20. Bossuyt PM, Reitsma JB, Bruns DE, Gatsonis CA, Glasziou PP, Irwig LM, et al. Toward complete and accurate reporting of studies of diagnostic accuracy. The STARD initiative. Am J Clin Pathol. 2003;119:18–22.

    Article  PubMed  Google Scholar 

  21. Cohen JF, Korevaar DA, Altman DG, Bruns DE, Gatsonis CA, Hooft L, et al. STARD 2015 guidelines for reporting diagnostic accuracy studies: explanation and elaboration. BMJ Open. 2016;6:e012799.

    Article  PubMed  PubMed Central  Google Scholar 

  22. Quintana DS, Alvares GA, Heathers JAJ. Guidelines for Reporting Articles on Psychiatry and Heart rate variability (GRAPH): recommendations to advance research communication. Transl Psychiatry. 2016;6:e803.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  23. Dobbs WC, Fedewa MV, MacDonald HV, Holmes CJ, Cicone ZS, Plews DJ, et al. The accuracy of acquiring heart rate variability from portable devices: a systematic review and meta-analysis. Sports Med. 2019;49:417–35.

    Article  PubMed  Google Scholar 

  24. Grässler B, Thielmann B, Böckelmann I, Hökelmann A. Effects of different training interventions on heart rate variability and cardiovascular health and risk factors in young and middle-aged adults: a systematic review: 1090. Front Physiol. 2021;12:532.

    Article  Google Scholar 

  25. Darius S, Hohmann CB, Siegel L, Böckelmann I. Assessment of psychological stress in kindergarten teachers with varying degrees of overcommitment. [Beurteilung psychischer Beanspruchung bei Kindergartenerzieherinnen mit unterschiedlichem Overcommitment]. Psychiatr Prax. 2021.

  26. Borchini R, Ferrario MM, Bertù L, Veronesi G, Bonzini M, Dorso M, et al. Prolonged job strain reduces time-domain heart rate variability on both working and resting days among cardiovascular-susceptible nurses. Int J Occup Med Environ Health. 2015;28:42–51.

    Article  PubMed  Google Scholar 

  27. Borchini R, Veronesi G, Bonzini M, Gianfagna F, Dashi O, Ferrario MM. Heart rate variability frequency domain alterations among healthy nurses exposed to prolonged work stress. Int J Environ Res Public Health. 2018.

  28. Jarczok MN, Koenig J, Li J, Mauss D, Hoffmann K, Schmidt B, et al. The association of work stress and glycemic status is partially mediated by autonomic nervous system function: cross-sectional results from the Mannheim Industrial Cohort Study (MICS). PLoS One. 2016;11:e0160743.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  29. Loerbroks A, Schilling O, Haxsen V, Jarczok MN, Thayer JF, Fischer JE. The fruits of ones labor: effort-reward imbalance but not job strain is related to heart rate variability across the day in 35-44-year-old workers. J Psychosom Res. 2010;69:151–9.

    Article  PubMed  Google Scholar 

  30. Hintsanen M, Elovainio M, Puttonen S, Kivimaki M, Koskinen T, Raitakari OT, et al. Effort-reward imbalance, heart rate, and heart rate variability: the Cardiovascular Risk in Young Finns Study. Int J Behav Med. 2007;14:202–12. .

    Article  PubMed  Google Scholar 

  31. Eller NH, Blønd M, Nielsen M, Kristiansen J, Netterstrøm B. Effort reward imbalance is associated with vagal withdrawal in Danish public sector employees. Int J Psychophysiol. 2011;81:218–24.

    Article  PubMed  Google Scholar 

  32. Uusitalo A, Mets T, Martinmäki K, Mauno S, Kinnunen U, Rusko H. Heart rate variability related to effort at work. Appl Ergon. 2011;42:830–8.

    Article  PubMed  Google Scholar 

  33. Garza JL, Cavallari JM, Eijckelhof B, Huysmans MA, Thamsuwan O, Johnson PW, et al. Office workers with high effort-reward imbalance and overcommitment have greater decreases in heart rate variability over a 2-h working period. Int Arch Occup Environ Health. 2015;88(5):565–75 0340-0131.

    Article  PubMed  Google Scholar 

  34. Landolt K, Maruff P, Horan B, Kingsley M, Kinsella G, O'Halloran PD, et al. Chronic work stress and decreased vagal tone impairs decision making and reaction time in jockeys. Psychoneuroendocrinology. 2017;84:151–8.

    Article  PubMed  Google Scholar 

Download references


Not applicable.


No funding was received for conducting this study. Open Access funding enabled and organized by Projekt DEAL.

Author information

Authors and Affiliations



All authors contributed to the study conception and design. JH and BT were the reviewers of the articles. The first draft of the manuscript was written by BT and all authors commented on previous versions of the manuscript. The authors read and approved the final manuscript.

Corresponding author

Correspondence to Beatrice Thielmann.

Ethics declarations

Ethics approval and consent to participate

No study was performed on humans.

Consent for publication

Not applicable.

Competing interests

The authors have no financial or proprietary interests in any material discussed in this article.

Additional information

Publisher’s Note

Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Supplementary Information

Additional file 1: Supplement 1

. Results of the STARDHRV evaluation of included publications.

Rights and permissions

Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit The Creative Commons Public Domain Dedication waiver ( applies to the data made available in this article, unless otherwise stated in a credit line to the data.

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Thielmann, B., Hartung, J. & Böckelmann, I. Objective assessment of mental stress in individuals with different levels of effort reward imbalance or overcommitment using heart rate variability: a systematic review. Syst Rev 11, 48 (2022).

Download citation

  • Received:

  • Accepted:

  • Published:

  • DOI: